Biometrics is the study of automated methods for uniquely associating humans with measurements of their intrinsic physical, biochemical, or behavioral traits, for example, fingerprints, face, iris, DNA, gait, etc. Biometric fusion, by intelligently combining information from multiple modalities in decision-making, has proven to be effective in improving accuracy and robustness in both biometric authentication and biometric recognition (identification and verification).
Knowing the quality of biometric samples via biometric quality assessment is useful in validating the quality of the acquired samples, and thus ensuring good recognition performance. More importantly, with assessed biometric quality scores available, quality-based biometric fusion, a more robust biometric fusion scheme, can be performed.
The quality of a biometric sample, e.g., a fingerprint image, a facial image, etc., can be assessed subjectively or objectively. While subjective assessment is based on human conception of biometric sample quality, objective assessment is to determine the quality algorithmically. With the number of applications for biometrics increasing, there is an increasing demand for more accurate and more robust recognition. Therefore, more effective objective quality assessment technologies are needed.